Active Iterative Social Inference in Multi-Trial Signaling Games.

Human behavioral choices can reveal intrinsic and extrinsic decision-influencing factors. We investigate the inference of choice priors in situations of referential ambiguity. In particular, we use the scenario of signaling games and investigate to which extent study participants profit from actively engaging in the task. Previous work has revealed that speakers are able to infer listeners' choice priors upon observing ambiguity resolution. However, it was also shown that only a small group of participants was able to strategically construct ambiguous situations to create learning opportunities. This paper sets to address how prior inference unfolds in more complex learning scenarios. In Experiment 1, we examine whether participants accumulate evidence about inferred choice priors across a series of four consecutive trials. Despite the intuitive simplicity of the task, information integration turns out to be only partially successful. Integration errors result from a variety of sources, including transitivity failure and recency bias. In Experiment 2, we investigate how the ability to actively construct learning scenarios affects the success of prior inference and whether the iterative settings improve the ability to choose utterances strategically. The results suggest that full task engagement and explicit access to the reasoning pipeline facilitates the invocation of optimal utterance choices as well as the accurate inference of listeners' choice priors.

Learning about others: Modeling social inference through ambiguity resolution.

Bayesian accounts of social cognition successfully model the human ability to infer goals and intentions of others on the basis of their behavior. In this paper, we extend this paradigm to the analysis of ambiguity resolution during brief communicative exchanges. In a reference game experimental setup, we observed that participants were able to infer listeners' preferences when analyzing their choice of object given referential ambiguity. Moreover, a subset of speakers was able to strategically choose ambiguous over unambiguous utterances in an epistemic manner, although a different group preferred unambiguous utterances. We show that a modified Rational Speech Act model well-approximates the data of both the inference of listeners' preferences and their utterance choices. In particular, the observed preference inference is modeled by Bayesian inference, which computes posteriors over hypothetical, behavior-influencing inner states of conversation partners-such as their knowledge, beliefs, intentions, or preferences-after observing their utterance-interpretation behavior. Utterance choice is modeled by anticipating social information gain, which we formalize as the expected knowledge change, when choosing a particular utterance and watching the listener's response. Taken together, our results demonstrate how social conversations allow us to (sometimes strategically) learn about each other when observing interpretations of ambiguous utterances.

Event-Predictive Cognition: A Root for Conceptual Human Thought.

Our minds navigate a continuous stream of sensorimotor experiences, selectively compressing them into events. Event-predictive encodings and processing abilities have evolved because they mirror interactions between agents and objects-and the pursuance or avoidance of critical interactions lies at the heart of survival and reproduction. However, it appears that these abilities have evolved not only to pursue live-enhancing events and to avoid threatening events, but also to distinguish food sources, to produce and to use tools, to cooperate, and to communicate. They may have even set the stage for the formation of larger societies and the development of cultural identities. Research on event-predictive cognition investigates how events and conceptualizations thereof are learned, structured, and processed dynamically. It suggests that event-predictive encodings and processes optimally mediate between sensorimotor processes and language. On the one hand, they enable us to perceive and control physical interactions with our world in a highly adaptive, versatile, goal-directed manner. On the other hand, they allow us to coordinate complex social interactions and, in particular, to comprehend and produce language. Event-predictive learning segments sensorimotor experiences into event-predictive encodings. Once first encodings are formed, the mind learns progressively higher order compositional structures, which allow reflecting on the past, reasoning, and planning on multiple levels of abstraction. We conclude that human conceptual thought may be grounded in the principles of event-predictive cognition constituting its root.